Example usage for org.opencv.objdetect CascadeClassifier CascadeClassifier

Introduction

In this page you can find the example usage for org.opencv.objdetect CascadeClassifier CascadeClassifier.

Prototype

public CascadeClassifier() 

Source Link

Usage

From source file:com.ibm.streamsx.edgevideo.device.FaceDetector.java

License:Open Source License

/**
 * Create a new instance using the specified {@link CascadeClassifier}.
 * @param faceClassifierPath path to the classifier - e.g. haarcascade_frontalface_alt.xml
 * @throws IOException /*from   ww w. j  a v a  2 s . c o m*/
 */
public FaceDetector(File faceClassifierPath) throws IOException {
    CascadeClassifier faceClassifier = new CascadeClassifier();
    boolean loaded = faceClassifier.load(faceClassifierPath.toString());
    if (!loaded) {
        throw new IOException("Error loading face classifier path: " + faceClassifierPath);
    }
    this.faceClassifier = faceClassifier;
}

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From source file:detectors.CCdetection.java

/**
 * Method to scan image with x classifier
 *//*from   ww  w .  j  a v a2 s . c om*/
public void scanImage(String path) {
    CascadeClassifier faceCC = new CascadeClassifier();
    faceCC.load("res/haarcascade_frontalface_alt.xml");

    //Matrix to hold image to be scanned
    Mat image = new Mat();
    image = Highgui.imread(path, IMREAD_COLOR);

    Mat rgb = new Mat();
    Mat gray = new Mat();
    image.copyTo(rgb);
    image.copyTo(gray);

    //Create integral image from the grayscale version of frame 
    Imgproc.cvtColor(rgb, gray, Imgproc.COLOR_BGR2GRAY);
    Imgproc.equalizeHist(gray, gray);

    //MatOfRect detection window initialized
    MatOfRect detects = new MatOfRect();
    faceCC.detectMultiScale(gray, detects);

    //Print out number of detected rect objects detected
    if (detects.toArray().length != 0) {
        System.out.printf("Detected %s\n", detects.toArray().length);
    }
}

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From source file:detectors.CCdetection.java

/**
 * Method to scan video with x classifier
 * NOT COMPLETE//from  ww  w .  j  ava  2 s. c  o  m
 */
public void scanVideo() {
    //Initialize video capture object to 0(default camera device)
    VideoCapture vc = new VideoCapture(0);

    //String path = "";

    //Initialize and load in classifier
    CascadeClassifier faceCC = new CascadeClassifier();
    faceCC.load("res/haarcascade_frontalface_default.xml");

    //Matrix(opencv core image object) to hold the image frame coming from the capture stream
    Mat image = new Mat();

    boolean isFound = false;
    while (!isFound) {
        //VideoCapture read combines grab and retrieve methods to decode and return the frame
        vc.read(image);
        if (image != null) {

            //Initialize new Mats to hold the original colored frame and the grayscaled frame
            Mat rgb = new Mat();
            Mat gray = new Mat();
            image.copyTo(rgb);
            image.copyTo(gray);

            //Create integral image from the grayscale version of frame 
            Imgproc.cvtColor(rgb, gray, Imgproc.COLOR_BGR2GRAY);
            Imgproc.equalizeHist(gray, gray);

            //MatOfRect detection window initialized
            MatOfRect detects = new MatOfRect();
            faceCC.detectMultiScale(gray, detects);

            //Print out number of detected rect objects detected
            if (detects.toArray().length != 0) {
                System.out.printf("Detected %s\n", detects.toArray().length);
                //prodFound(UPC,"T");
                isFound = true;
            }

        } else {
            break;
        }
    }
}

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From source file:org.pidome.client.userdetection.faces.FD_Controller.java

/**
 * Init the controller variables// w ww .j  a  v a 2 s.c  o  m
 */
public final void init() {
    this.capture = new VideoCapture();
    this.faceCascade = new CascadeClassifier();
    this.absoluteFaceSize = 0;
}

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From source file:org.pidome.client.userdetection.faces.FD_Controller.java

/**
 * When the Haar checkbox is selected, deselect the other one and load the
 * proper XML classifier//from w ww  .j av a  2 s .  c  o m
 *
 */
@FXML
protected void haarSelected() {
    // check whether the lpb checkbox is selected and deselect it
    if (this.lbpClassifier.isSelected()) {
        this.lbpClassifier.setSelected(false);
    }
    this.faceCascade = new CascadeClassifier();
    this.checkboxSelection("lib/opencv/haarcascade_frontalface_alt.xml");
}

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From source file:org.pidome.client.video.capture.faces.recognition.FaceDetection.java

public FaceDetection() {
    this.faceCascade = new CascadeClassifier();
    this.faceCascade.load("lib/opencv/haarcascade_frontalface_alt.xml");
}

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From source file:org.wso2.carbon.cep.objectdetection.siddhiextension.ObjectDetectionExtension.java

License:Open Source License

/**
 * Detect objects using OpenCV.//from  w  w  w .j a  v a  2 s  . c o  m
 *
 * @param imageHex
 *            the image hex string
 * @param cascadePath
 *            the cascade path
 * @return the detected object count
 */
private long detectObjects(String imageHex, String cascadePath) {
    long objectCount = 0;
    try {
        // conversion to Mat
        byte[] imageByteArr = (byte[]) new Hex().decode(imageHex);
        Mat image = Highgui.imdecode(new MatOfByte(imageByteArr), Highgui.IMREAD_UNCHANGED);

        // initializing classifier
        CascadeClassifier cClassifier = new CascadeClassifier();
        cClassifier.load(cascadePath);

        // pre-processing
        Imgproc.cvtColor(image, image, Imgproc.COLOR_RGB2GRAY);
        Imgproc.equalizeHist(image, image);

        // detecting objects
        MatOfRect imageRect = new MatOfRect();
        cClassifier.detectMultiScale(image, imageRect);

        // image count
        objectCount = ((Integer) imageRect.toList().size()).longValue();
    } catch (DecoderException e) {
        e.printStackTrace();
    }

    return objectCount;
}

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